The 7 Most Common Data Visualization Mistakes

Posted on December 21, 2015 | Updated on January 25, 2023

Data visualization is a fundamental aspect of data analysis today. Anything from the average U.S. citizen’s social media usage to the salaries of professional sports players to the latest 2016 presidential election poll results can be visually displayed for public understanding. While data visualization is an excellent tool for simplifying mass amounts of information, some do not always use it properly. In these cases, it becomes confusing and complex. Below are seven common data visualization mistakes to consider next time you’re designing an infographic:

1. Something Does Not Add Up

It may seem like the simplest component of any data visualization, but in some instances, the numbers don’t add up. Pie charts and bar graphs should always add up to 100. Consider the image below.


Do those numbers look off to you? They do not add up to 100 percent, but rather 188 percent. Not only is this confusing for the reader, it does not reflect well on whoever published this pie chart.

A pie chart might not have been the best option for displaying the results of this survey, as the percentages do not seem to display the data correctly. Be sure to double-check your numbers when generating a pie chart or other form of visualization. It may seem like it goes unsaid, but we still see mistakes like the one shown above.

2. Disappearing Axes

A line chart or bar graph that is missing one of its axes presents more confusion and problems for readers. It does not put the data in context and, in turn, presents a distorted picture. The image below provides an excellent example.


Since the y-axis is completely missing from this chart, I have no idea what these percentages are in reference to. When creating a graph or chart, always be sure to include both axes. You could even have a third party take a look at your visualization to ensure your audience will take what you want them to take from it.

3. Choosing the Wrong Format

It’s very important to consider what type of visualization best illustrates the point you are trying to make. In some instances, it might be a pie chart. In others, it might be a line graph. The visualization below might not have been the best choice to represent these survey responses.


The designer did not arrange the percentages in descending order and this isn’t the best visual representation of them. A pie chart, however, could have been a better way of displaying the survey results to highlight the disparities among the percentages.

When choosing which type of visualization to use, keep your end point in mind. What will get your point across in the best way?

4. Scales Don’t Make Sense

Inaccurate scales in a visualization misrepresent data. Whether it’s a bubble chart, pie chart or bar graph, the scales must accurately reflect the data they’re displaying.


The visualization above contains a misrepresentative scale. 71.9 percent looks larger than 77.1 percent, 74.5 percent looks less than 73.3 percent. The data appears inaccurate and just confuses the reader. Be sure to check that your visuals are in accurate scale. Providing numbers is helpful, but a correctly scaled visual is much easier to read.

5. Trying to Do Too Much

It can be tempting to include lots of information in an infographic. It might seem like the best possible way to convey a mass amount at once. However, it only confuses the reader and buries your main points.

The visualization below details social media usage across platforms and years. It seems to want to depict the growth in these platforms over the years, but instead presents us with statistics on usage of these platforms, with no year specified.

The graphic is also very busy-looking and, consequently, it’s hard to decipher the main points. Consider what information is essential when putting your visualization together. If the reader doesn’t need it to understand your main points, don’t include it.


6. Difficult to Compare

If your visualization is comparing data across any category, your readers must be able to easily decipher it. Try to avoid steeping your comparison in the design of your graphic.


The graphic above makes it difficult to compare the waste management patterns of countries around the world. Though the world map makes for a nice visual, it would be much easier to compare these patterns if the designer places these bars next to each other.

If you are creating a visualization with comparison data, consider which arrangement makes the comparison easiest to understand. Remove any unnecessary design or visual elements.

7. Counterintuitive Arrangements

You should always aim to arrange your data in an intuitive manner. Arranging your bars in alphabetical or descending order and ordering your pie charts in descending order counterclockwise or clockwise.

These intuitive arrangements draw the reader’s eye to the numbers they need to interpret and make for a cleaner look to your graphic overall.


The designer of the visualization above did not arrange the data intuitively. The 28 percent bar should be after the 45 percent bar, followed by the 21 percent bar.

It may seem like a small mistake, but rearranging it makes a great difference in drawing a reader’s eye. So keep your own instincts in mind when arranging your data.

Avoid These Top Data Visualization Mistakes

When creating your next data visualization, keep your end goal and your instincts in mind when trying to avoid these data visualization mistakes. Think of what makes the most sense for what you are trying to get across. Keep it simple and you won’t be seeing your graphics on a list like this.

About The Author

Eleanor Hecks is the Editor-in-Chief of Designerly Magazine, an online publication dedicated to providing in-depth content from the design and marketing industries. When she's not designing or writing code, you can find her exploring the outdoors with her husband and dog in their RV, burning calories at a local Zumba class, or curled up with a good book with her cats Gem and Cali.

You can find more of Eleanor's work at


  1. DevDigital on January 22, 2016 at 6:16 am

    Data visualization is not about making a pretty chart or graph, however, it’s far more than that. By visualizing information it is turned “into a landscape that you can explore with your eyes, a kind of map, really, a sort of information map. And when you’re lost in information, an information map is kind of useful.”

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